Race-Specific Genetic Profiles of Homologous Recombination Deficiency in Multiple Cancers

Homologous recombination deficiency (HRD) has been used to predict both cancer prognosis and the response to DNA-damaging therapies in many cancer types. HRD has diverse manifestations in different cancers and even in different populations. Many screening strategies have been designed for detecting the sensitivity of a patient’s HRD status to targeted therapies. However, these approaches suffer from low sensitivity, and are not specific to each cancer type and population group. Therefore, identifying race-specific and targetable HRD-related genes is of clinical importance. Here, we conducted analyses using genomic sequencing data that was generated by the Pan-Cancer Atlas. Collapsing non-synonymous variants with functional damage to HRD-related genes, we analyzed the association between these genes and race within cancer types using the optimal sequencing kernel association test (SKAT-O). We have identified race-specific mutational patterns of curated HRD-related genes across cancers. Overall, more significant mutation sites were found in ATM, BRCA2, POLE, and TOP2B in both the ‘White’ and ‘Asian’ populations, whereas PTEN, EGFG, and RIF1 mutations were observed in both the ‘White’ and ‘African American/Black’ populations. Furthermore, supported by pathogenic tendency databases and previous reports, in the ‘African American/Black’ population, several associations, including BLM with breast invasive carcinoma, ERCC5 with ovarian serous cystadenocarcinoma, as well as PTEN with stomach adenocarcinoma, were newly described here. Although several HRD-related genes are common across cancers, many of them were found to be specific to race. Further studies, using a larger cohort of diverse populations, are necessary to identify HRD-related genes that are specific to race, for guiding gene testing methods.

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Pan-cancer landscape of homologous recombination deficiency

10.1101/2020.01.13.905026 ◽

2020 ◽

Cited By ~ 5

Author(s):

Luan Nguyen ◽

John Martens ◽

Arne Van Hoeck ◽

Edwin Cuppen

Keyword(s):

Prostate Cancer ◽

Homologous Recombination ◽

Cancer Genomics ◽

Strand Break ◽

Diagnostic Value ◽

Cancer Type ◽

Brca1 And Brca2 ◽

Homologous Recombination Deficiency ◽

A Genome ◽

Pan Cancer

AbstractHomologous recombination deficiency (HRD) results in impaired double strand break repair and is a frequent driver of tumorigenesis. Here, we developed a genome-wide mutational scar-based pan-cancer Classifier of HOmologous Recombination Deficiency (CHORD) that can discriminate BRCA1- and BRCA2-subtypes. Analysis of a metastatic (n=3,504) and primary (n=1,854) pan-cancer cohort revealed HRD was most frequent in ovarian and breast cancer, followed by pancreatic and prostate cancer. Biallelic inactivation of BRCA1, BRCA2, RAD51C or PALB2 was the most common genetic cause of HRD, with RAD51C and PALB2 inactivation resulting in BRCA2-type HRD. While the specific genetic cause of HRD was cancer type specific, biallelic inactivation was predominantly associated with loss-of-heterozygosity (LOH), with increased contribution of deep deletions in prostate cancer. Our results demonstrate the value of pan-cancer genomics-based HRD testing and its potential diagnostic value for patient stratification towards treatment with e.g. poly ADP-ribose polymerase inhibitors (PARPi).

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Prevalence and Outcome of COVID-19 Infection in Cancer Patients: A National Veterans Affairs Study

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djaa159 ◽

2020 ◽

Cited By ~ 1

Author(s):

Nathanael R Fillmore ◽

Jennifer La ◽

Raphael E Szalat ◽

David P Tuck ◽

Vinh Nguyen ◽

...

Keyword(s):

African American ◽

Cancer Patients ◽

Hematologic Malignancy ◽

Statistical Tests ◽

Veterans Affairs ◽

Attributable Mortality ◽

Cancer Type ◽

The Us ◽

Charlson Comorbidity Score ◽

Cancer Types

Abstract Background Emerging data suggest variability in susceptibility and outcome to coronavirus disease 2019 (COVID-19) infection. Identifying risk factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations. Methods We analyzed electronic health records of the US Veterans Affairs Healthcare System and assessed the prevalence of COVID-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for COVID-19 who were positive, as well as outcome attributable to COVID-19, and stratified by clinical characteristics including demographics, comorbidities, cancer treatment, and cancer type. All statistical tests are 2-sided. Results Of 22 914 cancer patients tested for COVID-19, 1794 (7.8%) were positive. The prevalence of COVID-19 was similar across age. Higher prevalence was observed in African American (15.0%) compared with White (5.5%; P < .001) and in patients with hematologic malignancy compared with those with solid tumors (10.9% vs 7.8%; P < .001). Conversely, prevalence was lower in current smokers and patients who recently received cancer therapy (<6 months). The COVID-19–attributable mortality was 10.9%. Higher attributable mortality rates were observed in older patients, those with higher Charlson comorbidity score, and in certain cancer types. Recent (<6 months) or past treatment did not influence attributable mortality. Importantly, African American patients had 3.5-fold higher COVID-19–attributable hospitalization; however, they had similar attributable mortality as White patients. Conclusion Preexistence of cancer affects both susceptibility to COVID-19 infection and eventual outcome. The overall COVID-19–attributable mortality in cancer patients is affected by age, comorbidity, and specific cancer types; however, race or recent treatment including immunotherapy do not impact outcome.

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Pan-cancer landscape of homologous recombination deficiency

Nature Communications ◽

10.1038/s41467-020-19406-4 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Luan Nguyen ◽

John W. M. Martens ◽

Arne Van Hoeck ◽

Edwin Cuppen

Keyword(s):

Prostate Cancer ◽

Homologous Recombination ◽

Cancer Genomics ◽

Strand Break ◽

Diagnostic Value ◽

Cancer Type ◽

Homologous Recombination Deficiency ◽

Genome Wide ◽

A Genome ◽

Pan Cancer

Abstract Homologous recombination deficiency (HRD) results in impaired double strand break repair and is a frequent driver of tumorigenesis. Here, we develop a genome-wide mutational scar-based pan-cancer Classifier of HOmologous Recombination Deficiency (CHORD) that can discriminate BRCA1- and BRCA2-subtypes. Analysis of a metastatic (n = 3,504) and primary (n = 1,854) pan-cancer cohort reveals that HRD is most frequent in ovarian and breast cancer, followed by pancreatic and prostate cancer. We identify biallelic inactivation of BRCA1, BRCA2, RAD51C or PALB2 as the most common genetic cause of HRD, with RAD51C and PALB2 inactivation resulting in BRCA2-type HRD. We find that while the specific genetic cause of HRD is cancer type specific, biallelic inactivation is predominantly associated with loss-of-heterozygosity (LOH), with increased contribution of deep deletions in prostate cancer. Our results demonstrate the value of pan-cancer genomics-based HRD testing and its potential diagnostic value for patient stratification towards treatment with e.g. poly ADP-ribose polymerase inhibitors (PARPi).

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Genomic aberration based molecular signatures efficiently characterize homologous recombination deficiency in prostate cancer

10.1101/681114 ◽

2019 ◽

Cited By ~ 1

Author(s):

Zsofia Sztupinszki ◽

Miklos Diossy ◽

Marcin Krzystanek ◽

Judit Borcsok ◽

Mark Pomerantz ◽

...

Keyword(s):

Prostate Cancer ◽

Homologous Recombination ◽

Parp Inhibitor ◽

Next Generation Sequencing Data ◽

Parp Inhibition ◽

Sequencing Data ◽

Mutational Signatures ◽

Homologous Recombination Deficiency ◽

Platinum Based Chemotherapy ◽

Inhibitor Treatment

AbstractBackgroundProstate cancers with mutations in genes involved in homologous recombination (HR), most commonly BRCA2, respond favorably to PARP inhibition and platinum-based chemotherapy. It is not clear, however, whether other prostate tumors that do not harbor deleterious mutations in these particular genes can similarly be deficient in HR, rendering them sensitive to HR-directed therapies.To identify a more comprehensive set of prostate cancer cases with homologous recombination deficiency (HRD) including those cases that do not harbor mutations in known HR genes.HRD levels can be estimated using various mutational signatures derived from next-generation sequencing data. We used this approach to determine whether prostate cancer cases display clear signs of HRD in somatic tumor biopsies. Whole genome (n=311) and whole exome sequencing data (n=498) of both primary and metastatic prostate adenocarcinomas (PRAD) were analyzed.ResultsKnown BRCA-deficient samples showed robust signs of HR-deficiency associated mutational signatures. HRD-patterns were also detected in a subset of patients who did not harbor germline or somatic mutations in BRCA1/2 or other HR related genes. Patients with HRD signatures had a significantly worse prognosis than patients without signs of HRD.ConclusionsThese findings may expand the number of cases likely to respond to PARP-inhibitor treatment. Based on the HRD associated mutational signatures, 5-8 % of prostate cancer cases may be good candidates for PARP-inhibitor treatment (including those with BRCA1/2 mutations).

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Higher prevalence of homologous recombination-deficiency in lung squamous carcinoma from African Americans

10.1101/651794 ◽

2019 ◽

Author(s):

Sanju Sinha ◽

Khadijah A. Mitchell ◽

Adriana Zingone ◽

Elise Bowman ◽

Neelam Sinha ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Squamous Carcinoma ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Homologous Recombination Deficiency ◽

Molecular Features ◽

Incidence And Mortality ◽

Cancer Types ◽

Lung Squamous Carcinoma

AbstractTo improve our understanding of the longstanding disparities in incidence and mortality across multiple cancer types among minority populations, we performed a systematic comparative analysis of molecular features in tumors from African American (AA) and European American (EA) ancestry. Our pan-cancer analysis on the cancer genome atlas (TCGA) and a more focused analysis of genome-wide somatic copy number profiles integrated with tumor-normal RNA sequencing in a racially balanced cohort of 222 non-small cell lung cancers (NSCLC) reveals more aggressive genomic characteristics of AA tumors. In general, we find AA tumors exhibit higher genomic instability (GI), homologous recombination-deficiency (HRD) levels, and more aggressive molecular features such as chromothripsis across many cancer types, including lung squamous carcinoma (LUSC). GI and HRD levels are strongly correlated across AA tumors, indicating that HRD plays an important role in GI in these patients. The prevalence of germline HRD is higher in AA tumors, suggesting that the somatic differences observed have genetic ancestry origins. Finally, we identify AA-specific copy number-based arm, focal and gene level recurrent features in lung cancer, including a higher frequency of PTEN deletion and KRAS amplification and a lower frequency of CDKN2A deletion. These results highlight the importance of including minority and under-represented populations in genomics research and may have therapeutic implications.

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Rate of incidental germline findings detected by tumor-normal matched sequencing in cancer types lacking hereditary cancer testing guidelines.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.10582 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 10582-10582

Author(s):

Timothy A. Yap ◽

Arya Ashok ◽

Jessica Stoll ◽

Anna Ewa Schwarzbach ◽

Kimberly L. Blackwell ◽

...

Keyword(s):

Bile Duct ◽

Hereditary Cancer ◽

Next Generation Sequencing Data ◽

Cancer Type ◽

Cancer Genes ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Germline Variants ◽

Cancer Types ◽

Germline Testing

10582 Background: Up to 10% of all cancers are associated with hereditary cancer syndromes; however, guidelines for germline testing are currently limited to patients and families with specific cancer types (ovarian, breast, prostate, pancreatic, etc.). Although germline alterations have been shown in genes associated with cancers such as bile-duct, head & neck, brain, bladder, esophageal, and lung cancers, genetic testing is not routinely offered (PMID: 28873162). In such cancers, a guidelines-based approach may fail to detect cancer risk variants found by tumor-normal (T/N) matched sequencing. Here, we report the prevalence of incidental germline findings in patients with the aforementioned 6 cancer types and highlight frequently mutated genes by cancer type. Methods: We retrospectively analyzed next-generation sequencing data from de-identified records of 19,630 patients tested using Tempus|xT T/N matched assay. Incidental germline findings (i.e., single nucleotide variants and small insertions/deletions) detected in 50 hereditary cancer genes were determined for: bile duct (n = 466), head & neck (n = 673), esophageal (n = 395), brain (n = 1,391), bladder (n = 810), and lung (n = 5,544), where n = total patients. For comparison, we also included 4 cancer types that frequently undergo germline testing: ovarian (n = 2,042), breast (n = 3,542), prostate (n = 2,146), and pancreatic (n = 2,621). Results: We detected incidental pathogenic/likely pathogenic germline variants (P/LPV) in 6.5% (601/9,279) of patients diagnosed with the 6 selected cancer types lacking hereditary cancer testing guidelines. The highest prevalence of P/LPV was identified in patients with bladder (8%), brain (6.9%), and lung (6.5%) cancers. Frequently mutated genes (Table) include ATM (n = 62), BRCA2 (n = 60), BRCA1 (n = 33), APC (n = 27), and CHEK2 (n = 21). Of note, the Ashkenazi Jewish variant (p.I1307K) was the most frequent mutation in APC. For cancer types where patients frequently undergo germline testing, the rates of incidental germline findings in descending order were ovarian (15%), breast (12%), prostate (9.4%), and pancreatic (8.5%) cancers. Conclusions: In addition to enhanced variant calling, T/N matched sequencing may identify germline variants missed by a guidelines-based approach to testing. The identification of such germline findings may have clinical implications for the patient, as well as at-risk family members, thereby resulting in the opportunity for genetic counseling and risk-stratified intervention.[Table: see text]

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Integrative Analysis of Cancer Omics Data for Prognosis Modeling

Genes ◽

10.3390/genes10080604 ◽

2019 ◽

Vol 10 (8) ◽

pp. 604 ◽

Cited By ~ 2

Author(s):

Wang ◽

Wu ◽

Keyword(s):

Integrative Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Sufficient Information ◽

Cancer Type ◽

Multiple Cancer ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Information Borrowing ◽

Penalization Technique

Prognosis modeling plays an important role in cancer studies. With the development of omics profiling, extensive research has been conducted to search for prognostic markers for various cancer types. However, many of the existing studies share a common limitation by only focusing on a single cancer type and suffering from a lack of sufficient information. With potential molecular similarity across cancer types, one cancer type may contain information useful for the analysis of other types. The integration of multiple cancer types may facilitate information borrowing so as to more comprehensively and more accurately describe prognosis. In this study, we conduct marginal and joint integrative analysis of multiple cancer types, effectively introducing integration in the discovery process. For accommodating high dimensionality and identifying relevant markers, we adopt the advanced penalization technique which has a solid statistical ground. Gene expression data on nine cancer types from The Cancer Genome Atlas (TCGA) are analyzed, leading to biologically sensible findings that are different from the alternatives. Overall, this study provides a novel venue for cancer prognosis modeling by integrating multiple cancer types.

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Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

Cancer Informatics ◽

10.4137/cin.s23862 ◽

2015 ◽

Vol 14 ◽

pp. CIN.S23862 ◽

Cited By ~ 7

Author(s):

Wikum Dinalankara ◽

Héctor Corrada Bravo

Keyword(s):

Gene Expression ◽

Normal Tissue ◽

Tissue Expression ◽

Cancer Prognosis ◽

Clinical Settings ◽

Cancer Type ◽

Genomic Signatures ◽

Normal Expression ◽

Gene Expression Signatures ◽

Cancer Types

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings.

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Contextual Classifications of Cancer Driver Genes

10.1101/715508 ◽

2019 ◽

Author(s):

Pramod Chandrashekar ◽

Navid Ahmadinejad ◽

Junwen Wang ◽

Aleksandar Sekulic ◽

Jan B. Egan ◽

...

Keyword(s):

Computational Method ◽

Cancer Type ◽

Sequencing Data ◽

Multiple Cancer ◽

Driver Genes ◽

Cancer Driver ◽

Link Type ◽

Mutational Hotspots ◽

Cancer Types ◽

Cancer Driver Genes

ABSTRACTFunctions of cancer driver genes depend on cellular contexts that vary substantially across tissues and organs. Distinguishing oncogenes (OGs) and tumor suppressor genes (TSGs) for each cancer type is critical to identifying clinically actionable targets. However, current resources for context-aware classifications of cancer drivers are limited. In this study, we show that the direction and magnitude of somatic selection of missense and truncating mutations of a gene are suggestive of its contextual activities. By integrating these features with ratiometric and conservation measures, we developed a computational method to categorize OGs and TSGs using exome sequencing data. This new method, named genes under selection in tumors (GUST) shows an overall accuracy of 0.94 when tested on manually curated benchmarks. Application of GUST to 10,172 tumor exomes of 33 cancer types identified 98 OGs and 179 TSGs, >70% of which promote tumorigenesis in only one cancer type. In broad-spectrum drivers shared across multiple cancer types, we found heterogeneous mutational hotspots modifying distinct functional domains, implicating the synchrony of convergent and divergent disease mechanisms. We further discovered two novel OGs and 28 novel TSGs with high confidence. The GUST program is available at https://github.com/liliulab/gust. A database with pre-computed classifications is available at https://liliulab.shinyapps.io/gust

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Adjuvant Capecitabine-Containing Chemotherapy Benefit and Homologous Recombination Deficiency Status Among Early-Stage TNBC Patients in the FinXX trial

10.21203/rs.3.rs-125140/v1 ◽

2020 ◽

Author(s):

Leonora W. de Boo ◽

Katarzyna Jóźwiak ◽

Heikki Joensuu ◽

Henrik Lindman ◽

Susanna Lauttia ◽

...

Keyword(s):

Adjuvant Chemotherapy ◽

Homologous Recombination ◽

Interaction Analysis ◽

Early Stage ◽

Predictive Biomarkers ◽

Next Generation Sequencing Data ◽

Comparative Genomic ◽

Sequencing Data ◽

Conventional Chemotherapy ◽

Homologous Recombination Deficiency

Abstract Background: Recent data demonstrate that patients with early-stage triple negative breast cancer (TNBC) benefit from escalating adjuvant treatment with capecitabine. However, since a substantial proportion of patients does not benefit, predictive biomarkers to select those individuals upfront are needed. Over half of all TNBCs have a BRCA1-like DNA copy number signature similar to the profile found in germline BRCA1-mutated breast cancers and indicative for homologous recombination deficiency. We evaluate this signature as a predictive biomarker for capecitabine benefit in archived specimens of the randomized controlled FinXX trial. Additionally, we compared the concordance of our DNA-based BRCA1-like classifier with the RNA-based NanoString BRCAness signature. Methods: Early-stage TNBC patients were randomized between adjuvant capecitabine-containing chemotherapy (TX+CEX: capecitabine plus docetaxel, followed by cyclophosphamide, epirubicin and capecitabine) and conventional adjuvant chemotherapy (T+CEF: docetaxel, followed by cyclophosphamide, epirubicin, and fluorouracil). Breast tumor BRCA1-like status was determined on low coverage, whole genome next-generation sequencing data using an established DNA comparative genomic hybridization algorithm. We used interaction analysis in proportional hazards models to evaluate whether benefit of adjuvant capecitabine-containing versus conventional chemotherapy differs between BRCA1-like and non-BRCA1-like tumors in early-stage TNBC patients.Results: For 129 (63.9%) of the 202 TNBC patients the BRCA1-like status could be determined. Thirty-five recurrences and 32 deaths occurred during a median follow-up of 10.7 years. The capecitabine effect on recurrence-free survival did not significantly differ between the 68 patients (52.7%) with a BRCA1-like tumor (HR 0.66, 95% CI 0.24-1.81) and others (HR 0.23, 95% CI 0.08-0.70, P interaction = 0.17), also after adjustment for clinico-pathological variables. Conclusions: In the FinXX trial, the BRCA1-like status was not associated with a differential benefit from capecitabine-containing adjuvant chemotherapy compared to conventional chemotherapy in the TNBC subgroup. Based on this study, it is unlikely that the BRCA1-like classifier can be used to distinguish patients who do and do not benefit from capecitabine-enriched standard adjuvant chemotherapy.

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